Penerapan Algoritma K-NN Pada Rekrutment Program Magang Keluar Negeri

 (*)Masdalifa Hasibuan Mail (Universias Budi Darma, Medan, Indonesia)
 Abdul Sani Sembiring (Universias Budi Darma, Medan, Indonesia)
 Ronda Deli Sianturi (Universias Budi Darma, Medan, Indonesia)

(*) Corresponding Author

Abstract

There are positive factors behind this program. In other words, a successful apprenticeship program can be a recruitment strategy that can be considered as a successful apprenticeship program can expand the reach to reach the best prospective workers. To solve this problem, a solution using data mining can help the problems above. One of the algorithms that will be used is the K-Nearest Neighbor (K-NN) algorithm. By making an algorithm, it can help make it easier for users to determine the selection of the best prospective workers who will be sent abroad. The algorithm used for data classification in data mining is the K-NN algorithm, which is a classification of a set of data. The benefit of this research is to provide the advantages of a more effective and efficient alternative. For the apprentice selection recomundation system. By applying are criteria such as goals for prospective workers to be even better and can be implemented as recommendations in the selection of apprentices

Keywords


Data Mining; Internship Recruitment Program; K-Neaters Neighbor Algorithm

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References

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